AI Ethics Roundtable
The Ethics and Early Career Committee would like to invite you and your students to our upcoming round table discussion on AI Ethics. This will take place virtually through Zoom on Friday, June 2nd at 9am Pacific / 10am Central / Noon Eastern (https://nu.zoom.us/j/2183621123).
Please join Dr. Nisheeth Vishnoi from Yale, Dr. David Danks from UC San Diego, and Dr. Hoda Heidari from Carnegie Mellon University as we discuss a variety of aspects of AI Ethics with our moderators Dr. Stefanie Jegelka from MIT and Dr. Jodi Reeves from National University. This event is a great opportunity for TILOS students to learn about the constantly evolving issues of AI Ethics in research and the societal impact of AI. It will also provide a platform for students to gain insights and valuable advice that can help them in their future career pursuits.
Nisheeth Vishnoi is the A. Bartlett Giamatti Professor of Computer Science and a co-founder of the Computation and Society Initiative at Yale University. He studies the foundations of computation, and his research spans several areas of theoretical computer science, optimization, and machine learning. He is also interested in understanding nature and society from a computational viewpoint. Here, his current focus includes understanding the emergence of intelligence and developing methods to address ethical issues at the interface of artificial intelligence and humanity.
David Danks is Professor of Data Science & Philosophy and affiliate faculty in Computer Science & Engineering at University of California, San Diego. His research interests range widely across philosophy, cognitive science, and machine learning, including their intersection. Danks has examined the ethical, psychological, and policy issues around AI and robotics across multiple sectors, including transportation, healthcare, privacy, and security. He has also done significant research in computational cognitive science and developed multiple novel causal discovery algorithms for complex types of observational and experimental data. Danks is the recipient of a James S. McDonnell Foundation Scholar Award, as well as an Andrew Carnegie Fellowship. He currently serves on multiple advisory boards, including the National AI Advisory Committee.
Hoda Heidari is an Assistant Professor in Machine Learning and Societal Computing at the School of Computer Science, Carnegie Mellon University. Her research is broadly concerned with the social, ethical, and economic implications of Artificial Intelligence. In particular, her research addresses issues of unfairness and accountability through Machine Learning. Her work in this area has won a best-paper award at the ACM Conference on Fairness, Accountability, and Transparency (FAccT) and an exemplary track award at the ACM Conference on Economics and Computation (EC). She has organized several scholarly events on topics related to Responsible and Trustworthy AI, including a tutorial at the Web Conference (WWW) and several workshops at the Neural and Information Processing Systems (NeurIPS) conference. Dr. Heidari completed her doctoral studies in Computer and Information Science at the University of Pennsylvania. She holds an M.Sc. degree in Statistics from the Wharton School of Business. Before joining Carnegie Mellon as a faculty member, she was a postdoctoral scholar at the Machine Learning Institute of ETH Zurich, followed by a year at the Artificial Intelligence, Policy, and Practice (AIPP) initiative at Cornell University.